Empirical Foundations of Science and Innovation Policy

There is little systematic evidence about the scientific and economic results of research inputs. One primary difficulty is the lack of a data infrastructure that can trace the empirical relationship between initial research funds, scientists who receive funding and the scientific and economic activities of scientists.

A new approach is being adopted to address this inadequacy based on a successful project in the United States, called STAR METRICS. Several countries are beginning to develop similar models. In addition, a Sloan Foundation funded project (ETOILE) is using STAR METRICS data to examine the activities of research teams in great detail, the TRICS projects at Imperial College is using a similar people centred approach to examine research teams, and a team of German researchers is investigating the potential of using Max Planck Institute data to describe German science.

A major challenge to these efforts is the challenge of working with fragmented research data and linking scientists to their activities. But parallel efforts could be leveraged. There are a wide variety of research management systems and systems like CrossRef, euroCRIS and CASRAI are working to agree on data dictionaries and identifiers. ORCID is working to create a unique identifier for researchers that could be used to unambiguously identify scientists.

The purpose of this workshop is begin to build a community of practice: to bring researchers and selected policy makers involved in each project to: